Sentence examples for both binary and multiclass from inspiring English sources

Typical pattern recognition applications require to handle both binary and multiclass classification problems.

Existing research suggests that a combination of carefully selected linear and nonlinear HRV features should significantly improve the accuracy for both binary and multiclass classification problems.

Moreover, TSG gives a new classification method with no demand for training, and it is in a simple unified form for both binary and multiclass cases.

OSDHL-RBFN is tested and evaluated in both static and dynamic environments on nine benchmark classification (binary and multiclass) problems for balanced, unbalanced, small, large, low dimensional and high dimensional datasets.

"A Simple Plug-in Bagging Ensemble Based on Threshold-moving for Classifying Binary and Multiclass Imbalanced Data". Collell, Guillem, Dražen Prelec, and Kaustubh R.Patil.

In general, balanced training data resulted in the lowest overall error rates for classification experiments (82.3% and 78.3% for the binary and multiclass experiments respectively).

We conducted experimental study on real-world classification (binary and multiclass) and regression problems with different scales among several relevant approaches: SSDAE-RR, ELM, DBN, neural network (NN), and SAE.

Thus, we briefly describe the corresponding binary and multiclass DCA-SVM as follows.

Extensive experiments were conducted using six binary and multiclass microarray datasets.

It's clear to see that binary and multiclass SVMs by nature are linear separable test methods for its optimal hyperplane construction.

We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets.